public class MaxAbsScaler extends Estimator<MaxAbsScalerModel> implements MaxAbsScalerParams, DefaultParamsWritable
Constructor and Description |
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MaxAbsScaler() |
MaxAbsScaler(String uid) |
Modifier and Type | Method and Description |
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MaxAbsScaler |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
MaxAbsScalerModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
inputCol()
Param for input column name.
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static MaxAbsScaler |
load(String path) |
Param<String> |
outputCol()
Param for output column name.
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static MLReader<T> |
read() |
MaxAbsScaler |
setInputCol(String value) |
MaxAbsScaler |
setOutputCol(String value) |
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
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String |
uid()
An immutable unique ID for the object and its derivatives.
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params
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
validateAndTransformSchema
getInputCol
getOutputCol
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString
write
save
$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize
public static MaxAbsScaler load(String path)
public static MLReader<T> read()
public final Param<String> outputCol()
HasOutputCol
outputCol
in interface HasOutputCol
public final Param<String> inputCol()
HasInputCol
inputCol
in interface HasInputCol
public String uid()
Identifiable
uid
in interface Identifiable
public MaxAbsScaler setInputCol(String value)
public MaxAbsScaler setOutputCol(String value)
public MaxAbsScalerModel fit(Dataset<?> dataset)
Estimator
fit
in class Estimator<MaxAbsScalerModel>
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
We check validity for interactions between parameters during transformSchema
and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public MaxAbsScaler copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Estimator<MaxAbsScalerModel>
extra
- (undocumented)